{"url":"/method/ebc","slug":"ebc","name":"EBC","full_name":"Enhanced Blockwise Classification","full_name_withheld":false,"description_markdown":"Traditional methods are based on block-wise regression. This framework, Enhanced Blockwise Classification (**EBC**), however, is based on the idea that aims to classify the count value within each block into several pre-defined bins. The enhancement comes from 3 aspects: discretization policy, label correction and loss function. \r\n\r\nNotice that the original block-wise classification concept was introduced by Liu *et al.* in *Counting Objects by Blockwise Classification*.","description_state":"present","introduced_year":null,"introduced_by":{"title":"CLIP-EBC: CLIP Can Count Accurately through Enhanced Blockwise Classification","paper":"/paper/clip-ebc-clip-can-count-accurately-through","first_author":"Yiming Ma","n_authors":3,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/clip-ebc-clip-can-count-accurately-through"},"source":{"url":"https://arxiv.org/abs/2403.09281v3","title":"CLIP-EBC: CLIP Can Count Accurately through Enhanced Blockwise Classification","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"Computer Vision","area_id":"computer-vision","collection":"Counting Methods","url":"/methods/category/counting-methods","pwc_aliases":[]}],"n_papers_tagged":4,"archive_num_papers":4,"papers_newest_first":[{"paper":"/paper/ebc-zip-improving-blockwise-crowd-counting","title":"EBC-ZIP: Improving Blockwise Crowd Counting with Zero-Inflated Poisson Regression","date":"2025-06-24","arxiv_id":"2506.19955","n_code_links":1,"syntology":null},{"paper":null,"title":"A neuromorphic camera for tracking passive and active matter with lower data throughput","date":"2025-01-13","arxiv_id":"2501.07230","n_code_links":0,"syntology":null},{"paper":"/paper/evrt-detr-the-surprising-effectiveness-of","title":"EvRT-DETR: Latent Space Adaptation of Image Detectors for Event-based Vision","date":"2024-12-03","arxiv_id":"2412.02890","n_code_links":1,"syntology":{"ran":3,"of":3,"unverified":0,"pointer_only":3}},{"paper":"/paper/clip-ebc-clip-can-count-accurately-through","title":"CLIP-EBC: CLIP Can Count Accurately through Enhanced Blockwise Classification","date":"2024-03-14","arxiv_id":"2403.09281","n_code_links":1,"syntology":null}],"papers_shown":4,"tasks":[{"task":"/task/crowd-counting","name":"Crowd Counting","papers":2},{"task":"/task/density-estimation","name":"Density Estimation","papers":2},{"task":"/task/classification-1","name":"Classification","papers":1},{"task":"/task/edge-computing","name":"Edge-computing","papers":1},{"task":"/task/event-detection","name":"Event Detection","papers":1},{"task":"/task/event-based-vision","name":"Event-based vision","papers":1},{"task":"/task/object","name":"Object","papers":1},{"task":"/task/object-detection","name":"Object Detection","papers":1},{"task":"/task/quantization","name":"Quantization","papers":1},{"task":"/task/image-classification","name":"image-classification","papers":1},{"task":"/task/object-detection-1","name":"object-detection","papers":1}],"tasks_shown":11,"n_tasks":11,"usage_by_year":[{"year":"2024","papers":2},{"year":"2025","papers":2}],"row_source":"methods_table","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/ebc"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}